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Data:
88.52 90.15 88.63 88.32 88.51 88.53 88.35 88.4 88.41 88.47 88.46 89.28 89.11 90.74 89.49 88.62 89.09 89.14 89.45 89.33 89.44 89.54 89.52 90.48 90.04 91.93 91.25 89.27 90.57 90.79 90.83 90.76 91.29 91.48 91.63 92.63 91.7 93.86 92.45 92.03 92.71 93.15 92.98 92.73 93.29 93.2 93.34 93.95 93.43 95.67 94.02 93.51 94.6 94.27 94.05 94.1 94.51 94.53 94.2 93.58 94.94 96.24 95.77 94.41 95.09 95.37 95.17 95.05 95.33 95.42 95.95 96.12 96.94 98.73 98.03 97.42 98.39 98.77 98.46 98.3 98.25 98.33 98.61 98.99 98.8 100.26 100.85 98.87 99.81 100.44 100.07 99.8 99.77 99.9 100.58 100.86 101.05 101.3 101.45 101.13 101.38 101.03 100.79 100.84 101.17 101.36 101.14 101.24
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R Code
library(Hmisc) m <- mean(x) e <- median(x) bitmap(file='test1.png') op <- par(mfrow=c(2,1)) mydensity1 <- density(x,kernel='gaussian',na.rm=TRUE) plot(mydensity1,main='Density Plot - Gaussian Kernel',xlab='Median (0 -> full line) | Mean (0 -> dashed line)',ylab='density') abline(v=e,lty=1) abline(v=m,lty=5) grid() myseq <- seq(0.01, 0.99, 0.01) hd <- hdquantile(x, probs = myseq, se = TRUE, na.rm = FALSE, names = TRUE, weights=FALSE) plot(myseq,hd,col=2,main='Harrell-Davis Quantiles',xlab='quantiles',ylab='Median (0 -> full) | Mean (0 -> dashed)') abline(h=m,lty=5) abline(h=e,lty=1) grid() par(op) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Median versus Mean',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,mean(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'median',header=TRUE) a<-table.element(a,median(x)) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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Computing time
1 seconds
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Big Analytics Cloud Computing Center
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